Search ga_ls9c_ard_3 whole collection

The proportion (from 0 to 100) of the dataset's valid data area that contains cloud pixels. For these ARD products, this value comes from the Fmask algorithm. from:

The proportion (from 0 to 100) of the dataset's valid data area that contains cloud pixels. For these ARD products, this value comes from the Fmask algorithm. to (exclusive):

Time when dataset was created (processed) From

Time when dataset was created (processed) to (exclusive)

The raw CRS string as it appears in metadata:

One of - final|interim|nrt (near real time):

ID of a dataset type:

Ground sampling distance of the sensor’s best resolution band in metres; represents the size (or spatial resolution) of one pixel. from:

Ground sampling distance of the sensor’s best resolution band in metres; represents the size (or spatial resolution) of one pixel. to (exclusive):

The azimuth angle of the sun at the moment of acquisition, in degree units measured clockwise from due north from:

The azimuth angle of the sun at the moment of acquisition, in degree units measured clockwise from due north to (exclusive):

The elevation angle of the sun at the moment of acquisition, in degree units relative to the horizon. from:

The elevation angle of the sun at the moment of acquisition, in degree units relative to the horizon. to (exclusive):

The proportion (from 0 to 100) of the dataset's valid data area that contains clear land pixels according to the Fmask algorithm from:

The proportion (from 0 to 100) of the dataset's valid data area that contains clear land pixels according to the Fmask algorithm to (exclusive):

The proportion (from 0 to 100) of the dataset's valid data area that contains cloud shadow pixels according to the Fmask algorithm from:

The proportion (from 0 to 100) of the dataset's valid data area that contains cloud shadow pixels according to the Fmask algorithm to (exclusive):

The proportion (from 0 to 100) of the dataset's valid data area that contains clear snow pixels according to the Fmask algorithm from:

The proportion (from 0 to 100) of the dataset's valid data area that contains clear snow pixels according to the Fmask algorithm to (exclusive):

The proportion (from 0 to 100) of the dataset's valid data area that contains clear water pixels according to the Fmask algorithm from:

The proportion (from 0 to 100) of the dataset's valid data area that contains clear water pixels according to the Fmask algorithm to (exclusive):

File format (GeoTiff, NetCDF):

GQA Circular error probable (90%) from:

GQA Circular error probable (90%) to (exclusive):

Mean of the absolute values of the x-axis (east-to-west) GCP residuals after removal of outliers, in pixel units based on a 25 metre resolution reference image (i.e. 0.2 = 5 metres) from:

Mean of the absolute values of the x-axis (east-to-west) GCP residuals after removal of outliers, in pixel units based on a 25 metre resolution reference image (i.e. 0.2 = 5 metres) to (exclusive):

Mean of the absolute values of the GCP residuals after removal of outliers, in pixel units based on a 25 metre resolution reference image (i.e. 0.2 = 5 metres) from:

Mean of the absolute values of the GCP residuals after removal of outliers, in pixel units based on a 25 metre resolution reference image (i.e. 0.2 = 5 metres) to (exclusive):

Mean of the absolute values of the y-axis (north-to-south) GCP residuals after removal of outliers, in pixel units based on a 25 metre resolution reference image (i.e. 0.2 = 5 metres) from:

Mean of the absolute values of the y-axis (north-to-south) GCP residuals after removal of outliers, in pixel units based on a 25 metre resolution reference image (i.e. 0.2 = 5 metres) to (exclusive):

Absolute value of the x-axis (east-to-west) GCP residuals, in pixel units based on a 25 metre resolution reference image (i.e. 0.2 = 5 metres) from:

Absolute value of the x-axis (east-to-west) GCP residuals, in pixel units based on a 25 metre resolution reference image (i.e. 0.2 = 5 metres) to (exclusive):

Absolute value of the total GCP residuals, in pixel units based on a 25 metre resolution reference image (i.e. 0.2 = 5 metres) from:

Absolute value of the total GCP residuals, in pixel units based on a 25 metre resolution reference image (i.e. 0.2 = 5 metres) to (exclusive):

Absolute value of the y-axis (north-to-south) GCP residuals, in pixel units based on a 25 metre resolution reference image (i.e. 0.2 = 5 metres) from:

Absolute value of the y-axis (north-to-south) GCP residuals, in pixel units based on a 25 metre resolution reference image (i.e. 0.2 = 5 metres) to (exclusive):

Circular error probable (90%) of the values of the GCP residuals, in pixel units based on a 25 metre resolution reference image (i.e. 0.2 = 5 metres) from:

Circular error probable (90%) of the values of the GCP residuals, in pixel units based on a 25 metre resolution reference image (i.e. 0.2 = 5 metres) to (exclusive):

Mean of the values of the x-axis (east-to-west) GCP residuals after removal of outliers, in pixel units based on a 25 metre resolution reference image (i.e. 0.2 = 5 metres) from:

Mean of the values of the x-axis (east-to-west) GCP residuals after removal of outliers, in pixel units based on a 25 metre resolution reference image (i.e. 0.2 = 5 metres) to (exclusive):

Mean of the values of the GCP residuals after removal of outliers, in pixel units based on a 25 metre resolution reference image (i.e. 0.2 = 5 metres) from:

Mean of the values of the GCP residuals after removal of outliers, in pixel units based on a 25 metre resolution reference image (i.e. 0.2 = 5 metres) to (exclusive):

Mean of the values of the y-axis (north-to-south) GCP residuals after removal of outliers, in pixel units based on a 25 metre resolution reference image (i.e. 0.2 = 5 metres) from:

Mean of the values of the y-axis (north-to-south) GCP residuals after removal of outliers, in pixel units based on a 25 metre resolution reference image (i.e. 0.2 = 5 metres) to (exclusive):

Standard Deviation of the values of the x-axis (east-to-west) GCP residuals after removal of outliers, in pixel units based on a 25 metre resolution reference image (i.e. 0.2 = 5 metres) from:

Standard Deviation of the values of the x-axis (east-to-west) GCP residuals after removal of outliers, in pixel units based on a 25 metre resolution reference image (i.e. 0.2 = 5 metres) to (exclusive):

Standard Deviation of the values of the GCP residuals after removal of outliers, in pixel units based on a 25 metre resolution reference image (i.e. 0.2 = 5 metres) from:

Standard Deviation of the values of the GCP residuals after removal of outliers, in pixel units based on a 25 metre resolution reference image (i.e. 0.2 = 5 metres) to (exclusive):

Standard Deviation of the values of the y-axis (north-to-south) GCP residuals after removal of outliers, in pixel units based on a 25 metre resolution reference image (i.e. 0.2 = 5 metres) from:

Standard Deviation of the values of the y-axis (north-to-south) GCP residuals after removal of outliers, in pixel units based on a 25 metre resolution reference image (i.e. 0.2 = 5 metres) to (exclusive):

Mean of the values of the x-axis (east-to-west) GCP residuals, in pixel units based on a 25 metre resolution reference image (i.e. 0.2 = 5 metres) from:

Mean of the values of the x-axis (east-to-west) GCP residuals, in pixel units based on a 25 metre resolution reference image (i.e. 0.2 = 5 metres) to (exclusive):

Mean of the values of the GCP residuals, in pixel units based on a 25 metre resolution reference image (i.e. 0.2 = 5 metres) from:

Mean of the values of the GCP residuals, in pixel units based on a 25 metre resolution reference image (i.e. 0.2 = 5 metres) to (exclusive):

Mean of the values of the y-axis (north-to-south) GCP residuals, in pixel units based on a 25 metre resolution reference image (i.e. 0.2 = 5 metres) from:

Mean of the values of the y-axis (north-to-south) GCP residuals, in pixel units based on a 25 metre resolution reference image (i.e. 0.2 = 5 metres) to (exclusive):

Standard Deviation of the values of the x-axis (east-to-west) GCP residuals, in pixel units based on a 25 metre resolution reference image (i.e. 0.2 = 5 metres) from:

Standard Deviation of the values of the x-axis (east-to-west) GCP residuals, in pixel units based on a 25 metre resolution reference image (i.e. 0.2 = 5 metres) to (exclusive):

Standard Deviation of the values of the GCP residuals, in pixel units based on a 25 metre resolution reference image (i.e. 0.2 = 5 metres) from:

Standard Deviation of the values of the GCP residuals, in pixel units based on a 25 metre resolution reference image (i.e. 0.2 = 5 metres) to (exclusive):

Standard Deviation of the values of the y-axis (north-to-south) GCP residuals, in pixel units based on a 25 metre resolution reference image (i.e. 0.2 = 5 metres) from:

Standard Deviation of the values of the y-axis (north-to-south) GCP residuals, in pixel units based on a 25 metre resolution reference image (i.e. 0.2 = 5 metres) to (exclusive):

Dataset UUID:

User who indexed the dataset:

When dataset was indexed:

Label:

A Landsat Collection 1 Level-1 product identifier including the Collection processing levels, processing date, collection number, and collection tier category (e.g. ‘LE07_L1TP_098084_20210307_20210308_02_RT’) :

A Landsat scene ID including WRS path and row, year and day, ground station identifier and archive version number (e.g. ‘LC80900852021066LGN00’) :

Latitude range from:

Latitude range to (exclusive):

Longitude range from:

Longitude range to (exclusive):

Full metadata document:

Metadata type name of dataset:

ID of a metadata type:

Spatial reference code from the provider. For Landsat region_code is a scene path row: '{:03d}{:03d}.format(path,row)' For Sentinel it is MGRS code. In general it is a unique string identifier that datasets covering roughly the same spatial region share. :

Acquisition time range From

Acquisition time range to (exclusive)

Dataset URI:

Add field

First 100 results (query limit)

Time (local)	Label
2021-10-31 11:10:24	ga_ls9c_ard_3-2-1_109070_2021-10-31_final.stac-item
2021-11-03 09:53:22	ga_ls9c_ard_3-2-1_096071_2021-11-03_final.stac-item
2021-11-11 10:17:27	ga_ls9c_ard_3-2-1_100072_2021-11-11_final.stac-item
2021-11-18 10:00:46	ga_ls9c_ard_3-2-1_097071_2021-11-18_final.stac-item
2021-12-13 09:22:36	ga_ls9c_ard_3-2-1_090089_2021-12-12_final.stac-item
2022-01-15 09:58:36	ga_ls9c_ard_3-2-1_097071_2022-01-15_final.stac-item
2022-01-19 09:40:41	ga_ls9c_ard_3-2-1_093088_2022-01-19_final.stac-item
2022-01-24 09:53:39	ga_ls9c_ard_3-2-1_096074_2022-01-24_final.stac-item
2022-02-13 09:35:16	ga_ls9c_ard_3-2-1_092090_2022-02-13_final.stac-item
2022-02-14 11:51:49	ga_ls9c_ard_3-2-1_115076_2022-02-14_final.stac-item
2022-02-14 11:52:13	ga_ls9c_ard_3-2-1_115077_2022-02-14_final.stac-item
2022-03-03 09:22:18	ga_ls9c_ard_3-2-1_090089_2022-03-02_final.stac-item
2022-03-22 11:29:16	ga_ls9c_ard_3-2-1_111082_2022-03-22_final.stac-item
2022-03-24 09:40:00	ga_ls9c_ard_3-2-1_093087_2022-03-24_final.stac-item
2022-04-05 09:57:54	ga_ls9c_ard_3-2-1_097070_2022-04-05_final.stac-item
2022-04-16 11:18:09	ga_ls9c_ard_3-2-1_110070_2022-04-16_final.stac-item
2022-04-20 09:21:40	ga_ls9c_ard_3-2-1_090088_2022-04-19_final.stac-item
2022-04-22 10:42:10	ga_ls9c_ard_3-2-1_104073_2022-04-22_final.stac-item
2022-05-04 11:07:40	ga_ls9c_ard_3-2-1_108075_2022-05-04_final.stac-item
2022-05-05 10:09:14	ga_ls9c_ard_3-2-1_099068_2022-05-05_final.stac-item
2022-05-08 10:42:06	ga_ls9c_ard_3-2-1_104073_2022-05-08_final.stac-item
2022-05-21 10:09:02	ga_ls9c_ard_3-2-1_099068_2022-05-21_final.stac-item
2022-05-21 10:13:26	ga_ls9c_ard_3-2-1_099079_2022-05-21_final.stac-item
2022-05-25 11:25:12	ga_ls9c_ard_3-2-1_111073_2022-05-25_final.stac-item
2022-05-25 11:28:23	ga_ls9c_ard_3-2-1_111081_2022-05-25_final.stac-item
2022-05-28 11:58:06	ga_ls9c_ard_3-2-1_116078_2022-05-28_final.stac-item
2022-06-08 09:57:54	ga_ls9c_ard_3-2-1_097071_2022-06-08_final.stac-item
2022-06-13 11:57:23	ga_ls9c_ard_3-2-1_116076_2022-06-13_final.stac-item
2022-06-15 10:02:58	ga_ls9c_ard_3-2-1_098068_2022-06-15_final.stac-item
2022-06-30 11:04:02	ga_ls9c_ard_3-2-1_107081_2022-06-30_final.stac-item
2022-07-12 09:45:49	ga_ls9c_ard_3-2-1_095071_2022-07-12_final.stac-item
2022-07-18 09:12:22	ga_ls9c_ard_3-2-1_089080_2022-07-17_final.stac-item
2022-08-01 11:02:14	ga_ls9c_ard_3-2-1_107076_2022-08-01_final.stac-item
2022-08-03 09:12:36	ga_ls9c_ard_3-2-1_089080_2022-08-02_final.stac-item
2022-08-03 10:49:05	ga_ls9c_ard_3-2-1_105074_2022-08-03_final.stac-item
2022-08-09 11:52:57	ga_ls9c_ard_3-2-1_115079_2022-08-09_final.stac-item
2022-08-25 11:53:02	ga_ls9c_ard_3-2-1_115079_2022-08-25_final.stac-item
2022-09-11 09:22:32	ga_ls9c_ard_3-2-1_090089_2022-09-10_final.stac-item
2022-09-14 11:25:10	ga_ls9c_ard_3-2-1_111071_2022-09-14_final.stac-item
2022-09-28 11:42:24	ga_ls9c_ard_3-2-1_113083_2022-09-28_final.stac-item
2022-09-30 11:30:02	ga_ls9c_ard_3-2-1_111083_2022-09-30_final.stac-item
2022-10-22 10:49:52	ga_ls9c_ard_3-2-1_105075_2022-10-22_final.stac-item
2022-10-25 11:24:21	ga_ls9c_ard_3-2-1_110084_2022-10-25_final.stac-item
2022-11-07 09:12:57	ga_ls9c_ard_3-2-1_089080_2022-11-06_final.stac-item
2022-11-09 10:39:29	ga_ls9c_ard_3-2-1_103080_2022-11-09_final.stac-item
2022-11-09 10:40:17	ga_ls9c_ard_3-2-1_103082_2022-11-09_final.stac-item
2022-11-15 09:57:38	ga_ls9c_ard_3-2-1_097068_2022-11-15_final.stac-item
2022-11-15 11:38:07	ga_ls9c_ard_3-2-1_113072_2022-11-15_final.stac-item
2022-11-22 10:06:36	ga_ls9c_ard_3-2-1_098075_2022-11-22_final.stac-item
2022-11-23 09:10:59	ga_ls9c_ard_3-2-1_089075_2022-11-22_final.stac-item
2022-11-28 09:34:41	ga_ls9c_ard_3-2-1_092088_2022-11-28_final.stac-item
2022-12-03 11:24:30	ga_ls9c_ard_3-2-1_111069_2022-12-03_final.stac-item
2022-12-06 10:19:20	ga_ls9c_ard_3-2-1_100076_2022-12-06_final.stac-item
2022-12-09 09:16:33	ga_ls9c_ard_3-2-1_089089_2022-12-08_final.stac-item
2022-12-09 10:49:51	ga_ls9c_ard_3-2-1_105075_2022-12-09_final.stac-item
2022-12-14 09:30:18	ga_ls9c_ard_3-2-1_092077_2022-12-14_final.stac-item
2022-12-14 11:06:00	ga_ls9c_ard_3-2-1_108069_2022-12-14_final.stac-item
2022-12-17 09:58:24	ga_ls9c_ard_3-2-1_097070_2022-12-17_final.stac-item
2022-12-22 11:58:59	ga_ls9c_ard_3-2-1_116078_2022-12-22_final.stac-item
2022-12-25 09:12:55	ga_ls9c_ard_3-2-1_089080_2022-12-24_final.stac-item
2022-12-31 10:13:58	ga_ls9c_ard_3-2-1_099078_2022-12-31_final.stac-item
2022-12-31 11:52:03	ga_ls9c_ard_3-2-1_115076_2022-12-31_final.stac-item
2023-01-15 11:08:20	ga_ls9c_ard_3-2-1_108075_2023-01-15_final.stac-item
2023-01-17 09:21:50	ga_ls9c_ard_3-2-1_090087_2023-01-16_final.stac-item
2023-01-18 11:37:59	ga_ls9c_ard_3-2-1_113072_2023-01-18_final.stac-item
2023-01-19 10:42:44	ga_ls9c_ard_3-2-1_104073_2023-01-19_final.stac-item
2023-01-25 10:05:43	ga_ls9c_ard_3-2-1_098073_2023-01-25_final.stac-item
2023-01-26 09:16:30	ga_ls9c_ard_3-2-1_089089_2023-01-25_final.stac-item
2023-01-29 09:41:51	ga_ls9c_ard_3-2-1_094075_2023-01-29_final.stac-item
2023-01-31 09:31:55	ga_ls9c_ard_3-2-1_092081_2023-01-31_final.stac-item
2023-02-01 11:51:40	ga_ls9c_ard_3-2-1_115075_2023-02-01_final.stac-item
2023-02-02 09:23:10	ga_ls9c_ard_3-2-1_090090_2023-02-01_final.stac-item
2023-03-27 11:12:08	ga_ls9c_ard_3-2-1_109070_2023-03-27_final.stac-item
2023-03-31 09:12:04	ga_ls9c_ard_3-2-1_089079_2023-03-30_final.stac-item
2023-04-05 09:33:48	ga_ls9c_ard_3-2-1_092087_2023-04-05_final.stac-item
2023-04-22 10:16:09	ga_ls9c_ard_3-2-1_099085_2023-04-22_final.stac-item
2023-04-24 11:41:52	ga_ls9c_ard_3-2-1_113083_2023-04-24_final.stac-item
2023-04-29 10:19:27	ga_ls9c_ard_3-2-1_100078_2023-04-29_final.stac-item
2023-04-29 11:57:32	ga_ls9c_ard_3-2-1_116076_2023-04-29_final.stac-item
2023-05-02 09:11:49	ga_ls9c_ard_3-2-1_089079_2023-05-01_final.stac-item
2023-05-02 10:51:30	ga_ls9c_ard_3-2-1_105081_2023-05-02_final.stac-item
2023-05-12 09:46:26	ga_ls9c_ard_3-2-1_095073_2023-05-12_final.stac-item
2023-06-19 09:15:50	ga_ls9c_ard_3-2-1_089090_2023-06-18_final.stac-item
2023-06-29 09:51:25	ga_ls9c_ard_3-2-1_095086_2023-06-29_final.stac-item
2023-06-29 09:51:48	ga_ls9c_ard_3-2-1_095087_2023-06-29_final.stac-item
2023-07-05 09:12:50	ga_ls9c_ard_3-2-1_089082_2023-07-04_final.stac-item
2023-07-05 09:15:38	ga_ls9c_ard_3-2-1_089089_2023-07-04_final.stac-item
2023-07-06 11:35:48	ga_ls9c_ard_3-2-1_112084_2023-07-06_final.stac-item
2023-07-18 10:18:30	ga_ls9c_ard_3-2-1_100076_2023-07-18_final.stac-item
2023-07-22 09:51:23	ga_ls9c_ard_3-2-1_096070_2023-07-22_final.stac-item
2023-08-02 09:39:44	ga_ls9c_ard_3-2-1_093087_2023-08-02_final.stac-item
2023-08-03 11:58:18	ga_ls9c_ard_3-2-1_116078_2023-08-03_final.stac-item
2023-08-04 09:22:13	ga_ls9c_ard_3-2-1_091074_2023-08-03_final.stac-item
2023-08-06 09:16:15	ga_ls9c_ard_3-2-1_089090_2023-08-05_final.stac-item
2023-10-22 11:58:26	ga_ls9c_ard_3-2-1_116077_2023-10-22_final.stac-item
2023-10-28 09:46:25	ga_ls9c_ard_3-2-1_094087_2023-10-28_final.stac-item
2023-11-17 09:17:41	ga_ls9c_ard_3-2-1_090077_2023-11-16_final.stac-item
2023-11-25 11:46:31	ga_ls9c_ard_3-2-1_114078_2023-11-25_final.stac-item
2023-11-26 09:12:01	ga_ls9c_ard_3-2-1_089078_2023-11-25_final.stac-item
2024-02-20 11:51:45	ga_ls9c_ard_3-2-1_115076_2024-02-20_final.stac-item

Return to ga_ls9c_ard_3 whole collection overview

ga_ls9c_ard_3: Geoscience Australia Landsat 9 Operational Land Imager and Thermal Infra-Red Scanner Analysis Ready Data Collection 3

Baseline satellite data

Inland water

Land and vegetation

Sea, ocean and coast

Hazards

Other products

All years